Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis. (arXiv:2203.16369v2 [cs.CL] UPDATED)

Aspect-based sentiment analysis (ABSA) predicts sentiment polarity towards a
specific aspect in the given sentence. While pre-trained language models such
as BERT have achieved great success, incorporating dynamic semantic changes
into ABSA remains challenging. To this end, in this paper, we propose to
address this problem by Dynamic Re-weighting BERT (DR-BERT), a novel method
designed to learn dynamic aspect-oriented semantics for ABSA. Specifically, we
first take the Stack-BERT layers as a primary encoder to grasp the overall
semantic of the …

analysis arxiv language language model semantics sentiment sentiment analysis